HunchLab applies risk modeling and AI to help forecast when and where crimes are likely to emerge and recommends specific patrol missions and tactics that can deter these events, according to a press release.

ShotSpotter will now go to market with HunchLab under the trademark “ShotSpotter Missions,” which is billed as “a proactive patrol management solution that goes beyond traditional hotspot modeling and builds upon the experiential knowledge of patrol officers.”

In addition to historical crime data, the SaaS solution is said to use current and future indicators that are run through advanced statistical models and machine learning to forecast potential crime incidents based on specific locations and times.

It analyzes factors such as seasonality, time of day, day of week, trends in socioeconomic conditions and upcoming events to create a risk analysis that helps inform patrol missions by shift, according to the announcement. The application breaks a city into 250 square-meter “cells” and gives guidance on when to patrol that cell, what crime type is likely to occur, and what patrol tactics to use. Officers no longer must be in an area hour after hour to have effective deterrence, the company states.

“The HunchLab technology provides a proven, high-value, and complementary solution we can immediately offer to our existing law enforcement customers,” states Ralph A. Clark, president and CEO of ShotSpotter. “We believe our investment will democratize the sharing of important intelligence with patrol officers who currently have limited direct access to crime analysts. ShotSpotter Missions provides officers in the field with their own personal virtual crime analyst to plan the most strategic and efficient patrol missions in an effort to reduce crime.”

ShotSpotter states that it plans to integrate Missions with gunfire data to enable it to update predictive models and patrol missions in real time. The application will be offered as an add-on product to the company’s gunfire detection solution, as well as a stand-alone application.

Along with the acquisition, the company plans to invest in additional data science and development resources to continually improve the product as well as advance the use of AI technology to help make existing and new products better.

ShotSpotter states the all-cash acquisition is not expected to be material to its full year 2018 results. The company will provide additional details about the transaction during its third quarter earnings call, scheduled after market close on Nov. 13.

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